Preface

Like the previous one, the model of the UNED team used casing information, however, this information was represented by an embedding gen- erated during training phase.. The

The number of negation structures per class (shown in Table 3) shows that there are more negation structures in documents labeled with negative sentiment in the development set,

The results of the MEDDOCAN shared task and evaluation effort on automatic de-identification of sensitive information from texts in Spanish show that ad- vanced deep learning

Milagros Fernández-Gavilanes Universidad de Vigo Silvia García Méndez Universidad de Vigo Salud María Jiménez Zafra Universidad de Jaén Manuel Maña López Universidad de Huelva

Taking into account that we have not generated a specific model for each domain, due to the needs of the sys- tem presented, the differences between pre- cision and recall

This paper describes the negation cue detec- tion model approaches presented by UPC’s team for the NEGES 2018 workshop task 2 (negation cues detection) (Jim´ enez-Zafra et al.,

El an´ alisis de los enfoques aplicados hasta el momento en espa˜ nol permiti´ o detectar la necesidad de generar un corpus anotado con la negaci´ on y su ´ ambito para poder

Por ello, entendemos que el proceso de compilaci´ on de un corpus para la prevenci´ on del suicidio debe extenderse a todas las redes sociales posibles, con independencia de que est´